Central moments multiple relaxation time LBM for hemodynamic simulations in intracranial aneurysms: An in-vitro validation study using PIV and PC-MRI

The lattice Boltzmann method (LBM) has recently emerged as an efficient alternative to classical Navier-Stokes solvers. This is particularly true for hemodynamics in complex geometries. However, in its most basic formulation, i.e. with the so-called single relaxation time (SRT) collision operator, it has been observed to have a limited stability domain in the Courant/Fourier space, strongly constraining the minimum time-step and grid size. The development of improved collision models such as the multiple relaxation time (MRT) operator in central moments space has tremendously widened the stability domain, while allowing to overcome a number of other well-documented artifacts, therefore opening the door for simulations over a wider range of grid and time-step sizes. The present work focuses on implementing and validating a specific collision operator, the central Hermite moments multiple relaxation time model with the full expansion of the equilibrium distribution function, to simulate blood flows in intracranial aneurysms. The study further proceeds with a validation of the numerical model through different test-cases and against experimental measurements obtained via stereoscopic particle image velocimetry (PIV) and phase-contrast magnetic resonance imaging (PC-MRI). For a patient-specific aneurysm both PIV and PC-MRI agree fairly well with the simulation. Finally, low-resolution simulations were shown to be able to capture blood flow information with sufficient accuracy, as demonstrated through both qualitative and quantitative analysis of the flow field while leading to strongly reduced computation times. For instance in the case of the patient-specific configuration, increasing the grid-size by a factor of two led to a reduction of computation time by a factor of 14 with very good similarity indices still ranging from 0.83 to 0.88.

[1]  Thomas Redel,et al.  Rupture Risk of Small Unruptured Intracranial Aneurysms in Japanese Adults , 2019, Stroke.

[2]  R. Benzi,et al.  Lattice Gas Dynamics with Enhanced Collisions , 1989 .

[3]  Mitsuo Umezu,et al.  Experimental insights into flow impingement in cerebral aneurysm by stereoscopic particle image velocimetry: transition from a laminar regime , 2013, Journal of The Royal Society Interface.

[4]  Erlend Magnus Viggen,et al.  The Lattice Boltzmann Method: Principles and Practice , 2016 .

[5]  G. Janiga,et al.  Cerebral blood flow in a healthy Circle of Willis and two intracranial aneurysms: computational fluid dynamics versus four-dimensional phase-contrast magnetic resonance imaging. , 2014, Journal of biomechanical engineering.

[6]  H. Kwak,et al.  Patient-Specific Computational Fluid Dynamics in Ruptured Posterior Communicating Aneurysms Using Measured Non-Newtonian Viscosity : A Preliminary Study , 2019, Journal of Korean Neurosurgical Society.

[7]  H H Woo,et al.  Regarding “Aneurysm Rupture Following Treatment with Flow-Diverting Stents: Computational Hemodynamics Analysis of Treatment” , 2011, American Journal of Neuroradiology.

[8]  A. Algra,et al.  Prevalence of unruptured intracranial aneurysms, with emphasis on sex, age, comorbidity, country, and time period: a systematic review and meta-analysis , 2011, The Lancet Neurology.

[9]  Mohammad Mehdi Rashidi,et al.  Numerical simulation of flow over a square cylinder with upstream and downstream circular bar using lattice Boltzmann method , 2018 .

[10]  Thomas Redel,et al.  Bringing hemodynamic simulations closer to the clinics: A CFD prototype study for intracranial aneurysms , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[11]  Oliver Speck,et al.  Transient flow prediction in an idealized aneurysm geometry using data assimilation , 2019, Comput. Biol. Medicine.

[12]  D. d'Humières,et al.  Multiple–relaxation–time lattice Boltzmann models in three dimensions , 2002, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[13]  C. Putman,et al.  Aneurysm Rupture Following Treatment with Flow-Diverting Stents: Computational Hemodynamics Analysis of Treatment , 2010, American Journal of Neuroradiology.

[14]  Thomas Redel,et al.  Tomographic particle image velocimetry for the validation of hemodynamic simulations in an intracranial aneurysm , 2017, 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[15]  J. Korvink,et al.  Cascaded digital lattice Boltzmann automata for high Reynolds number flow. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  I. Tiselj,et al.  Lattice Boltzmann Method , 2022, Advanced Computational Techniques for Heat and Mass Transfer in Food Processing.

[17]  B. Chopard,et al.  Comprehensive comparison of collision models in the lattice Boltzmann framework: Theoretical investigations. , 2019, Physical review. E.

[18]  I. Karlin,et al.  Gibbs' principle for the lattice-kinetic theory of fluid dynamics. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  D. Holdsworth,et al.  PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models. , 2008, Journal of biomechanical engineering.

[20]  P. Lallemand,et al.  Theory of the lattice boltzmann method: dispersion, dissipation, isotropy, galilean invariance, and stability , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[21]  Olivier Brina,et al.  Towards the Clinical utility of CFD for assessment of intracranial aneurysm rupture – a systematic review and novel parameter-ranking tool , 2018, Journal of NeuroInterventional Surgery.

[22]  I. Karlin,et al.  Lattice Boltzmann method for simulation of compressible flows on standard lattices. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[23]  Bastien Chopard,et al.  Lattice Boltzmann method with regularized pre-collision distribution functions , 2006, Math. Comput. Simul..

[24]  Gábor Závodszky,et al.  Validation of a lattice Boltzmann method implementation for a 3D transient fluid flow in an intracranial aneurysm geometry , 2013 .

[25]  P. Alam ‘S’ , 2021, Composites Engineering: An A–Z Guide.

[26]  D. d'Humières,et al.  Two-relaxation-time Lattice Boltzmann scheme: About parametrization, velocity, pressure and mixed boundary conditions , 2008 .

[27]  Orestis Malaspinas,et al.  Palabos: Parallel Lattice Boltzmann Solver , 2020, Comput. Math. Appl..

[28]  G. Janiga,et al.  A review on the reliability of hemodynamic modeling in intracranial aneurysms: why computational fluid dynamics alone cannot solve the equation. , 2019, Neurosurgical focus.

[29]  Matthias Müller,et al.  Interactive blood simulation for virtual surgery based on smoothed particle hydrodynamics. , 2004, Technology and health care : official journal of the European Society for Engineering and Medicine.

[30]  D A Steinman,et al.  Non‐Newtonian versus numerical rheology: Practical impact of shear‐thinning on the prediction of stable and unstable flows in intracranial aneurysms , 2017, International journal for numerical methods in biomedical engineering.

[31]  Mohammad Hossein Saadat,et al.  Lattice Boltzmann model for compressible flows on standard lattices: Variable Prandtl number and adiabatic exponent. , 2019, Physical review. E.

[32]  Dong Ni,et al.  Particle-based simulation of blood flow and vessel wall interactions in virtual surgery , 2010, SoICT.

[33]  H Meng,et al.  CFD: Computational Fluid Dynamics or Confounding Factor Dissemination? The Role of Hemodynamics in Intracranial Aneurysm Rupture Risk Assessment , 2014, American Journal of Neuroradiology.

[34]  Bastien Chopard,et al.  Optimization of flow diverters for cerebral aneurysms , 2012, J. Comput. Sci..

[35]  Fernando Mut,et al.  CFD and PIV analysis of hemodynamics in a growing intracranial aneurysm , 2012, International journal for numerical methods in biomedical engineering.

[36]  Khalid M. Saqr,et al.  Evidence for non-Newtonian behavior of intracranial blood flow from Doppler ultrasonography measurements , 2018, Medical & Biological Engineering & Computing.

[37]  P. Asinari,et al.  Factorization symmetry in the lattice Boltzmann method , 2009, 0911.5529.

[38]  Herbert F. Voigt,et al.  IEEE Engineering in Medicine and Biology Society , 2019, IEEE Transactions on Biomedical Engineering.

[39]  S Saalfeld,et al.  Does the DSA reconstruction kernel affect hemodynamic predictions in intracranial aneurysms? An analysis of geometry and blood flow variations , 2017, Journal of NeuroInterventional Surgery.

[40]  Peter V. Coveney,et al.  HemeLB: A high performance parallel lattice-Boltzmann code for large scale fluid flow in complex geometries , 2008, Comput. Phys. Commun..

[41]  B. Shizgal,et al.  Generalized Lattice-Boltzmann Equations , 1994 .

[42]  Seyed Ali Hosseini,et al.  Theoretical and numerical analysis of the lattice kinetic scheme for complex-flow simulations. , 2019, Physical review. E.

[43]  L. Luo,et al.  Theory of the lattice Boltzmann method: From the Boltzmann equation to the lattice Boltzmann equation , 1997 .

[44]  Pierre Bouillot,et al.  Particle Imaging Velocimetry Evaluation of Intracranial Stents in Sidewall Aneurysm: Hemodynamic Transition Related to the Stent Design , 2014, PloS one.

[45]  David A Steinman,et al.  The Computational Fluid Dynamics Rupture Challenge 2013--Phase II: Variability of Hemodynamic Simulations in Two Intracranial Aneurysms. , 2015, Journal of biomechanical engineering.

[46]  Yuichi Murayama,et al.  Computational fluid dynamics as a risk assessment tool for aneurysm rupture. , 2019, Neurosurgical focus.

[47]  D. Thévenin,et al.  Compressibility in lattice Boltzmann on standard stencils: effects of deviation from reference temperature , 2020, Philosophical Transactions of the Royal Society A.

[48]  Peter V. Coveney,et al.  Analysing and modelling the performance of the HemeLB lattice-Boltzmann simulation environment , 2012, J. Comput. Sci..

[49]  Juan R Cebral,et al.  Computational fluid dynamics modeling of intracranial aneurysms: qualitative comparison with cerebral angiography. , 2007, Academic radiology.

[50]  P. Lallemand,et al.  Momentum transfer of a Boltzmann-lattice fluid with boundaries , 2001 .

[51]  Makoto Yamamoto,et al.  Verification of a research prototype for hemodynamic analysis of cerebral aneurysms , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[52]  Zhenhua Chai,et al.  Multi-GPU Based Lattice Boltzmann Method for Hemodynamic Simulation in Patient-Specific Cerebral Aneurysm , 2015 .

[53]  Santosh Ansumali,et al.  Single relaxation time model for entropic lattice Boltzmann methods. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[54]  P. Bhatnagar,et al.  A Model for Collision Processes in Gases. I. Small Amplitude Processes in Charged and Neutral One-Component Systems , 1954 .

[55]  Cass T. Miller,et al.  An evaluation of lattice Boltzmann schemes for porous medium flow simulation , 2006 .

[56]  H. Marquering,et al.  3D Cine Phase-Contrast MRI at 3T in Intracranial Aneurysms Compared with Patient-Specific Computational Fluid Dynamics , 2013, American Journal of Neuroradiology.

[57]  S. Hosseini Development of a lattice Boltzmann-based numerical method for the simulation of reacting flows , 2020 .

[58]  Danna Zhou,et al.  d. , 1840, Microbial pathogenesis.

[59]  M. Finck,et al.  Simulation of nasal flow by lattice Boltzmann methods , 2007, Comput. Biol. Medicine.

[60]  F Mut,et al.  Flow Conditions in the Intracranial Aneurysm Lumen Are Associated with Inflammation and Degenerative Changes of the Aneurysm Wall , 2017, American Journal of Neuroradiology.

[61]  J. Boon The Lattice Boltzmann Equation for Fluid Dynamics and Beyond , 2003 .

[62]  Mohammad Mehdi Rashidi,et al.  Numerical study of MHD nanofluid natural convection in a baffled U-shaped enclosure , 2019, International Journal of Heat and Mass Transfer.

[63]  Seyed Ali Hosseini,et al.  Stability of the lattice kinetic scheme and choice of the free relaxation parameter. , 2019, Physical review. E.

[64]  Adnan H Siddiqui,et al.  Methodology for Computational Fluid Dynamic Validation for Medical Use: Application to Intracranial Aneurysm. , 2017, Journal of biomechanical engineering.

[65]  J. Xiang,et al.  High WSS or Low WSS? Complex Interactions of Hemodynamics with Intracranial Aneurysm Initiation, Growth, and Rupture: Toward a Unifying Hypothesis , 2014, American Journal of Neuroradiology.

[66]  Laurent Navarro,et al.  Segmentation of the thrombus of giant intracranial aneurysms from CT angiography scans with lattice Boltzmann method , 2014, Medical Image Anal..

[67]  D F Kallmes,et al.  Point: CFD—Computational Fluid Dynamics or Confounding Factor Dissemination , 2012, American Journal of Neuroradiology.

[68]  Kannan Masilamani,et al.  Complex fluid simulations with the parallel tree-based Lattice Boltzmann solver Musubi , 2014, J. Comput. Sci..

[69]  Khalid M. Saqr,et al.  What does computational fluid dynamics tell us about intracranial aneurysms? A meta-analysis and critical review , 2019, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[70]  Philipp Berg,et al.  Comparison of intracranial aneurysm flow quantification techniques: standard PIV vs stereoscopic PIV vs tomographic PIV vs phase-contrast MRI vs CFD , 2018, Journal of NeuroInterventional Surgery.

[71]  B. Chopard,et al.  Lattice Boltzmann Simulations of Blood Flow: Non-Newtonian Rheology and Clotting Processes , 2005 .

[72]  S. Chikatamarla,et al.  Entropic multirelaxation lattice Boltzmann models for turbulent flows. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[73]  X. Yuan,et al.  Kinetic theory representation of hydrodynamics: a way beyond the Navier–Stokes equation , 2006, Journal of Fluid Mechanics.

[74]  D. Thévenin,et al.  Hybrid Lattice Boltzmann-finite difference model for low mach number combustion simulation , 2019, Combustion and Flame.

[75]  Khalid M. Saqr,et al.  Effects of wall compliance on multiharmonic pulsatile flow in idealized cerebral aneurysm models: comparative PIV experiments , 2020 .